{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6ba877c6-9964-40a4-9e52-9836cf73b563",
   "metadata": {},
   "source": [
    "# pandas5 - 统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8019720d-c8e2-400f-a52f-7796b6e28f18",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16c07e7c-6b83-4232-92a5-0fb2e3bb7b08",
   "metadata": {},
   "source": [
    "## 计算同比环比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c3a0a713-a1d7-4d08-886e-d866c9a5abaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>本月销售额</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>月份</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5409855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4608455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4164972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3996770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3239005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2817936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3501304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2948189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2632960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2375385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2385283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1691973</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      本月销售额\n",
       "月份         \n",
       "1   5409855\n",
       "2   4608455\n",
       "3   4164972\n",
       "4   3996770\n",
       "5   3239005\n",
       "6   2817936\n",
       "7   3501304\n",
       "8   2948189\n",
       "9   2632960\n",
       "10  2375385\n",
       "11  2385283\n",
       "12  1691973"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_df = pd.read_excel('data/2020年销售数据.xlsx')\n",
    "sales_df['月份'] = sales_df.销售日期.dt.month\n",
    "sales_df['销售额'] = sales_df.售价 * sales_df.销售数量\n",
    "result_df = sales_df.pivot_table(index='月份', values='销售额', aggfunc='sum')\n",
    "result_df.rename(columns={'销售额': '本月销售额'}, inplace=True)\n",
    "result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5a1a52b2-d0dd-4208-b1c5-f07b667b1813",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>本月销售额</th>\n",
       "      <th>上月销售额</th>\n",
       "      <th>环比</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>月份</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5409855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4608455</td>\n",
       "      <td>5409855.0</td>\n",
       "      <td>-0.148137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4164972</td>\n",
       "      <td>4608455.0</td>\n",
       "      <td>-0.096232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3996770</td>\n",
       "      <td>4164972.0</td>\n",
       "      <td>-0.040385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3239005</td>\n",
       "      <td>3996770.0</td>\n",
       "      <td>-0.189594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2817936</td>\n",
       "      <td>3239005.0</td>\n",
       "      <td>-0.129999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3501304</td>\n",
       "      <td>2817936.0</td>\n",
       "      <td>0.242507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2948189</td>\n",
       "      <td>3501304.0</td>\n",
       "      <td>-0.157974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2632960</td>\n",
       "      <td>2948189.0</td>\n",
       "      <td>-0.106923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2375385</td>\n",
       "      <td>2632960.0</td>\n",
       "      <td>-0.097827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2385283</td>\n",
       "      <td>2375385.0</td>\n",
       "      <td>0.004167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1691973</td>\n",
       "      <td>2385283.0</td>\n",
       "      <td>-0.290662</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      本月销售额      上月销售额        环比\n",
       "月份                              \n",
       "1   5409855        NaN       NaN\n",
       "2   4608455  5409855.0 -0.148137\n",
       "3   4164972  4608455.0 -0.096232\n",
       "4   3996770  4164972.0 -0.040385\n",
       "5   3239005  3996770.0 -0.189594\n",
       "6   2817936  3239005.0 -0.129999\n",
       "7   3501304  2817936.0  0.242507\n",
       "8   2948189  3501304.0 -0.157974\n",
       "9   2632960  2948189.0 -0.106923\n",
       "10  2375385  2632960.0 -0.097827\n",
       "11  2385283  2375385.0  0.004167\n",
       "12  1691973  2385283.0 -0.290662"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 单元格向下偏移一格\n",
    "result_df['上月销售额'] = result_df.本月销售额.shift(1)\n",
    "result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f0ab2e00-86ce-4c61-be6a-01bd42ff6c87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "</style>\n",
       "<table id=\"T_12cb4\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_12cb4_level0_col0\" class=\"col_heading level0 col0\" >本月销售额</th>\n",
       "      <th id=\"T_12cb4_level0_col1\" class=\"col_heading level0 col1\" >上月销售额</th>\n",
       "      <th id=\"T_12cb4_level0_col2\" class=\"col_heading level0 col2\" >环比</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >月份</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "      <td id=\"T_12cb4_row0_col0\" class=\"data row0 col0\" >5409855</td>\n",
       "      <td id=\"T_12cb4_row0_col1\" class=\"data row0 col1\" >--------</td>\n",
       "      <td id=\"T_12cb4_row0_col2\" class=\"data row0 col2\" >--------</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "      <td id=\"T_12cb4_row1_col0\" class=\"data row1 col0\" >4608455</td>\n",
       "      <td id=\"T_12cb4_row1_col1\" class=\"data row1 col1\" >5409855</td>\n",
       "      <td id=\"T_12cb4_row1_col2\" class=\"data row1 col2\" >-14.81%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "      <td id=\"T_12cb4_row2_col0\" class=\"data row2 col0\" >4164972</td>\n",
       "      <td id=\"T_12cb4_row2_col1\" class=\"data row2 col1\" >4608455</td>\n",
       "      <td id=\"T_12cb4_row2_col2\" class=\"data row2 col2\" >-9.62%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "      <td id=\"T_12cb4_row3_col0\" class=\"data row3 col0\" >3996770</td>\n",
       "      <td id=\"T_12cb4_row3_col1\" class=\"data row3 col1\" >4164972</td>\n",
       "      <td id=\"T_12cb4_row3_col2\" class=\"data row3 col2\" >-4.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "      <td id=\"T_12cb4_row4_col0\" class=\"data row4 col0\" >3239005</td>\n",
       "      <td id=\"T_12cb4_row4_col1\" class=\"data row4 col1\" >3996770</td>\n",
       "      <td id=\"T_12cb4_row4_col2\" class=\"data row4 col2\" >-18.96%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "      <td id=\"T_12cb4_row5_col0\" class=\"data row5 col0\" >2817936</td>\n",
       "      <td id=\"T_12cb4_row5_col1\" class=\"data row5 col1\" >3239005</td>\n",
       "      <td id=\"T_12cb4_row5_col2\" class=\"data row5 col2\" >-13.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "      <td id=\"T_12cb4_row6_col0\" class=\"data row6 col0\" >3501304</td>\n",
       "      <td id=\"T_12cb4_row6_col1\" class=\"data row6 col1\" >2817936</td>\n",
       "      <td id=\"T_12cb4_row6_col2\" class=\"data row6 col2\" >24.25%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "      <td id=\"T_12cb4_row7_col0\" class=\"data row7 col0\" >2948189</td>\n",
       "      <td id=\"T_12cb4_row7_col1\" class=\"data row7 col1\" >3501304</td>\n",
       "      <td id=\"T_12cb4_row7_col2\" class=\"data row7 col2\" >-15.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "      <td id=\"T_12cb4_row8_col0\" class=\"data row8 col0\" >2632960</td>\n",
       "      <td id=\"T_12cb4_row8_col1\" class=\"data row8 col1\" >2948189</td>\n",
       "      <td id=\"T_12cb4_row8_col2\" class=\"data row8 col2\" >-10.69%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "      <td id=\"T_12cb4_row9_col0\" class=\"data row9 col0\" >2375385</td>\n",
       "      <td id=\"T_12cb4_row9_col1\" class=\"data row9 col1\" >2632960</td>\n",
       "      <td id=\"T_12cb4_row9_col2\" class=\"data row9 col2\" >-9.78%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row10\" class=\"row_heading level0 row10\" >11</th>\n",
       "      <td id=\"T_12cb4_row10_col0\" class=\"data row10 col0\" >2385283</td>\n",
       "      <td id=\"T_12cb4_row10_col1\" class=\"data row10 col1\" >2375385</td>\n",
       "      <td id=\"T_12cb4_row10_col2\" class=\"data row10 col2\" >0.42%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_12cb4_level0_row11\" class=\"row_heading level0 row11\" >12</th>\n",
       "      <td id=\"T_12cb4_row11_col0\" class=\"data row11 col0\" >1691973</td>\n",
       "      <td id=\"T_12cb4_row11_col1\" class=\"data row11 col1\" >2385283</td>\n",
       "      <td id=\"T_12cb4_row11_col2\" class=\"data row11 col2\" >-29.07%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x22d152c9940>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 环比 = （本月销售额 - 上月销售额） / 上月销售额\n",
    "result_df['环比'] = (result_df.本月销售额 - result_df.上月销售额) / result_df.上月销售额\n",
    "result_df.style.format(\n",
    "    formatter={'上月销售额': '{:.0f}', '环比': '{:.2%}'},\n",
    "    na_rep='--------'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bc79fa78-9113-44c0-bf76-e1facb443ad7",
   "metadata": {},
   "outputs": [],
   "source": [
    "result_df.drop(columns=['上月销售额', '环比'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "287443bd-60ef-42bd-bad2-077b38eb938a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>本月销售额</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>月份</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5409855</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4608455</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4164972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3996770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3239005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2817936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3501304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2948189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2632960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2375385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2385283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1691973</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      本月销售额\n",
       "月份         \n",
       "1   5409855\n",
       "2   4608455\n",
       "3   4164972\n",
       "4   3996770\n",
       "5   3239005\n",
       "6   2817936\n",
       "7   3501304\n",
       "8   2948189\n",
       "9   2632960\n",
       "10  2375385\n",
       "11  2385283\n",
       "12  1691973"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c8b152fc-c042-4acc-ba45-b5d6bf14ef6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>本月销售额</th>\n",
       "      <th>环比</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>月份</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5409855</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4608455</td>\n",
       "      <td>-0.148137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4164972</td>\n",
       "      <td>-0.096232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3996770</td>\n",
       "      <td>-0.040385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3239005</td>\n",
       "      <td>-0.189594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2817936</td>\n",
       "      <td>-0.129999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3501304</td>\n",
       "      <td>0.242507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2948189</td>\n",
       "      <td>-0.157974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2632960</td>\n",
       "      <td>-0.106923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2375385</td>\n",
       "      <td>-0.097827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2385283</td>\n",
       "      <td>0.004167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1691973</td>\n",
       "      <td>-0.290662</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      本月销售额        环比\n",
       "月份                   \n",
       "1   5409855       NaN\n",
       "2   4608455 -0.148137\n",
       "3   4164972 -0.096232\n",
       "4   3996770 -0.040385\n",
       "5   3239005 -0.189594\n",
       "6   2817936 -0.129999\n",
       "7   3501304  0.242507\n",
       "8   2948189 -0.157974\n",
       "9   2632960 -0.106923\n",
       "10  2375385 -0.097827\n",
       "11  2385283  0.004167\n",
       "12  1691973 -0.290662"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 计算环比\n",
    "result_df['环比'] = result_df.pct_change()\n",
    "result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44de0df6-1a5a-4d72-a83f-30d6df0058a3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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